docstr: :param base_dict: A string dictionary of base information about the
                    dataset, including: name, digest, source, and source
                    type.
  :return: A string dictionary containing the following fields: name,
           digest, source, source type, schema (optional), profile
           (optional).
docstr_tok: [":","param","base_dict",":","A","string","dictionary","of","base","information","about","the","dataset",",","including",":","name",",","digest",",","source",",","and","source","type",".",":","return",":","A","string","dictionary","containing","the","following","fields",":","name",",","digest",",","source",",","source","type",",","schema","(","optional",")",",","profile","(","optional",")","."]
code: def _to_dict(self, base_dict: Dict[str, str]) -> Dict[str, str]:
      """
      :param base_dict: A string dictionary of base information about the
                        dataset, including: name, digest, source, and source
                        type.
      :return: A string dictionary containing the following fields: name,
               digest, source, source type, schema (optional), profile
               (optional).
      """
      return {
          **base_dict,
          "schema": json.dumps(
              {"mlflow_colspec": self.schema.to_dict()}
          ),
          "profile": json.dumps(self.profile),
      }
  
file_path: mlflow/tests/resources/mlflow-test-plugin/mlflow_test_plugin/dummy_dataset.py
imports: import json
  from typing import Any, Dict, List, Optional
  import numpy
  import pandas
  from mlflow.data.dataset import Dataset
  from mlflow.types import Schema
  from mlflow.types.utils import _infer_schema
  from mlflow_test_plugin.dummy_dataset_source import DummyDatasetSource
label_desc: Use image node_id 3 for calling the DummyDataset obj's underlying member method code with example usage: obj._to_dict(base_dict) and returns: dict